Percorrer por autor "Boaventura, Rui A. R."
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- Surface Water Quality Assessment of Lis River Using Multivariate Statistical MethodsPublication . Vieira, Judite S.; Pires, José C. M.; Martins, Fernando G.; Vilar, Vítor J. P.; Boaventura, Rui A. R.; Botelho, Cidália M. S.This study presents the application of multivariate statistical tools for the evaluation of spatial variations and the interpretation of water quality data obtained in a monitoring program of Lis river basin surface water, Portugal. Twenty-seven physicochemical and microbiological parameters were determined in six water sampling campaigns at 16 monitoring sites during the period from September 2003 to November 2006. Correlation analysis, principal component analysis, and cluster analysis were performed to evaluate the main water pollution sources and to characterize the spatial distribution of water pollution profiles in river basin. The results achieved with the statistical methodologies led to distinguish natural and anthropogenic pollution sources. Additionally, monitoring sites with similar water pollution profile were identified, indicating that some monitoring locations can be changed to 1improve the spatial characterization of water quality in the river basin. CBO, CQO, P, and N were identified as significant variables affecting spatial variations, namely in the Lis river middle reach. Besides the identification of main pollution sources, the applied statistical tools were able to identify spatial patterns of water pollution in Lis river basin, which further helps in the reassessment of the number and location of monitoring sites.
- Water quality in Lis river, PortugalPublication . Vieira, Judite; Fonseca, André; Vilar, Vítor J. P.; Boaventura, Rui A. R.; Botelho, Cidália M. S.In the past 30 years, the Lis river basin has been subjected to constant ecological disasters mainly due to piggery untreated wastewater discharges. The aim of this study was to evaluate the effect of existing domestic, agricultural, and industrial activities on the water quality, and to propose a watershed plan to protect and manage surface water resources within the Lis river basin. For this purpose, 16 monitoring stations have been strategically selected along the Lis river stretch and its main tributaries to evaluate the water quality in six different sampling periods (2003- 2006). All samples were characterized in terms of organic material, nutrients, chlorophyll, and pathogenic bacteria. Generally, the Lis river presents poor water quality, according to environmental quality standards for surface water, principally in terms of dissolved oxygen, biochemical oxygen demand, total nitrogen, and fecal coliform, which can be associated mainly with the contamination source from pig-breeding farms. © Springer Science+Business Media B.V. 2012.
- Water quality modelling of Lis River, PortugalPublication . Vieira, Judite; Fonseca, André; Vilar, Vítor J. P.; Boaventura, Rui A. R.; Botelho, Cidália M. S.The aim of the study was to predict the impact of flow conditions, discharges and tributaries on the water quality of Lis River using QUAL2Kw model. Calibration of the model was performed, based on data obtained in field surveys carried out in July 2004 and November 2006. Generally the model fitted quite well the experimental data. The results indicated a decrease of water quality in the downstream area of Lis River, after the confluence of Lena, Milagres and Amor tributaries, as a result of discharges of wastewaters containing degradable organics, nutrients and pathogenic organisms from cattle-raising wastewaters, domestic effluents and agricultural runoff. The water quality criteria were exceeded in these areas for dissolved oxygen, biochemical oxygen demand, total nitrogen and faecal coliforms. Water quality modelling in different scenarios showed that the impact of tributaries on the quality of Lis River water was quite negligible and mainly depends on discharges, which are responsible by an increase of almost 45, 13 and 44 % of ultimate carbonaceous biochemical oxygen demand (CBODu), ammonium nitrogen and faecal coliforms, for winter simulation, and 23, 33 and 36 % for summer simulation, respectively, when compared to the real case scenario.